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Predicting nurses’ adherence to chemical decontamination procedures: a transtheoretical model SEM analysis

Year: 2026

Type: article

Abstract: BACKGROUND: This study investigates the psychological determinants of nurses’ adherence to chemical decontamination procedures using the Transtheoretical Model (TTM) and structural equation modeling (SEM). The psychological determinants examined include the stages of change, processes of change, self-efficacy, and decisional balance (pros and cons). With hazardous material (HAZMAT) incidents posing escalating global threats, understanding these specific behavioral compliance mechanisms among frontline healthcare workers is critical for optimizing disaster preparedness. METHODS: A cross-sectional study of 561 nurses across 75 Iranian medical centers employed a validated TTM-based questionnaire assessing stages of change, processes of change, self-efficacy, and decisional balance. Bootstrapping SEM analysis (SmartPLS 4.0) evaluated direct/indirect effects, with robust validation via fit indices (SRMR = 0.08, CFI = 0.93) and reliability metrics (Cronbach’s α = 0.702–0.892). RESULTS: Processes of change emerged as the strongest predictor of protocol adherence (β = 0.338, P < 0.001), with behavioral sub-constructs (counterconditioning: β = 0.824; stimulus control: β = 0.891) driving compliance. Decisional balance (“pros”) showed non-significant influence (P = 0.594). Environmental (β = 0.957) and social cues (β = 0.944), as components of self-efficacy, dominated the model, highlighting situational over intrinsic factors. CONCLUSION: The study establishes that behavior formation through process-based interventions (e.g., stage-specific simulations, environmental cue reinforcement) surpasses motivational approaches. Findings mandate redesigned training programs to forge instinctual protocol execution in crises, advancing a new standard for behavioral readiness in emergency medicine.

Source: BMC Nursing

DOI: 10.1186/s12912-025-04268-2

Authors: Shandiz Moslehi, Mehdi Khezeli, Asghar Tavan, Nadia Sedri, Sajjad Narimani